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Related Questions
- What are some common techniques used to improve contextual understanding in language models?
- How do models balance the generation of coherent and fluent text with the need for contextual accuracy?
- Can you explain the impact of training data quality on the trade-off between fluency and contextual understanding in language models?
- What role does domain knowledge play in enabling models to generate text that is both fluent and contextually accurate?
- How do models handle cases where contextual understanding and fluency are in conflict, such as when generating text that requires both technical and non-technical vocabulary?
- What are some potential limitations of relying on large datasets to improve contextual understanding and fluency in language models?
- Can you discuss the relationship between model size and the trade-off between contextual understanding and fluency in generated text?
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